Analytische Chemie
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Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on instrumental design and operational parameters that require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In a presence of surface defects the temperature field is distorted in a specific manner that depends on a shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for process monitoring: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows a cautious inference that optical spectroscopy is capable of detecting a defect and, possibly, predicting its character, e.g. inner or protruding.
Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on an instrumental design and operational parameters, which require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In the presence of surface defects, the temperature field is distorted in a specific manner that depends on shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for monitoring the process: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows for a cautious inference that optical spectroscopy can detect surface defects and, possibly, predict their characters, e.g., inner or protruding.
Additive manufacturing by laser metal deposition (LMD) requires continuous online monitoring to ensure quality of printed parts. Optical emission spectroscopy (OES) is proposed for the online detection of printing defects by monitoring minute variations in the temperature of a printed spot during laser scan. A two-lens optical system is attached to a moving laser head and focused on a molten pool created on a substrate during LMD. The light emitted by the pool is collected by an ultraviolet–visible (UV–vis) spectrometer and processed.
Two metrics are used to monitor variations in the surface temperature: the spectrally integrated emission intensity and correlation coefficient. The variations in the temperature are introduced by artificial defects, shallow grooves, and holes of various widths and diameters carved on a substrate surface. The metrics show sufficient sensitivity for revealing the surface defects, except for the smallest
holes with an under-millimeter diameter. Additionally, numeric simulations are carried out for the detection of emission in the UV–vis and near-infrared (NIR) spectral ranges at various surface temperatures. It is concluded that both the metrics perform better in the NIR range. In general, this work demonstrates that spectrally resolved OES suits well for monitoring surface defects during 3D metal
printing.